Rasch Measurement Theory Analysis In R
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Rasch Measurement Theory Analysis In R
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Author : Stefanie Wind
language : en
Publisher: CRC Press
Release Date : 2022-06-07
Rasch Measurement Theory Analysis In R written by Stefanie Wind and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-07 with Mathematics categories.
Rasch Measurement Theory Analysis in R provides researchers and practitioners with a step-by-step guide for conducting Rasch measurement theory analyses using R. It includes theoretical introductions to major Rasch measurement principles and techniques, demonstrations of analyses using several R packages that contain Rasch measurement functions, and sample interpretations of results. Features: Accessible to users with relatively little experience with R programming Reproducible data analysis examples that can be modified to accommodate users’ own data Accompanying e-book website with links to additional resources and R code updates as needed Features dichotomous and polytomous (rating scale) Rasch models that can be applied to data from a wide range of disciplines This book is designed for graduate students, researchers, and practitioners across the social, health, and behavioral sciences who have a basic familiarity with Rasch measurement theory and with R. Readers will learn how to use existing R packages to conduct a variety of analyses related to Rasch measurement theory, including evaluating data for adherence to measurement requirements, applying the dichotomous, Rating Scale, Partial Credit, and Many-Facet Rasch models, examining data for evidence of differential item functioning, and considering potential interpretations of results from such analyses.
Rasch Models For Measurement
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Author : David Andrich
language : en
Publisher: SAGE
Release Date : 1988
Rasch Models For Measurement written by David Andrich and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with Reference categories.
Examines the use of Rasch measurement models in the social sciences. This lucid introduction first focuses on general principles, so the applications and algebra of the model can be readily understood. Andrich then connects Rasch models to common procedures for social science measurement. Avoiding polemics, Andrich′s presentation allows comparison between the Rasch models and other, better known measurement approaches. Rasch Models For Measurement concentrates on the simple logistic model, the most elementary and commonly used of the Rasch models. This excellent introduction uses one example from personality inventory throughout to provide continuity as the procedures and statistical arguments are explained. Essential reading for all researchers and students who use measurement models. "A valuable asset to those of us who are concerned with teaching measurement issues. . . . My only quibble is that we have had to wait so long for what is a clear, concise and very approachable introduction to a fairly complex area. . . . For its size this volume covers a lot of ground and it would seem to be an ideal book for postgraduate students with a special interest in psychometrics and professional psychologists who are concerned with measurement and assessment. . . . An ideal primer." --The Statistician "Rasch Models for Measurement is a concise introduction to the general principles, philosophy, and methods that underlie the approach to measurement developed by Georg Rasch (1960/1980). This book is a welcome addition to the Sage series on Quantitative Applications in the Social Sciences, or (as my students describe them) "the little green books." This series introduces methodological issues for individuals with limited backgrounds in statistics and mathematics, and Andrich has provided a useful resource for these individuals. . . . This book can be recommended for graduate students and colleagues who want a basic understanding of the Rasch model." --Applied Psychological Measurement
Introduction To Rasch Measurement
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Author : Everett V. Smith
language : en
Publisher: Jam Press
Release Date : 2004
Introduction To Rasch Measurement written by Everett V. Smith and has been published by Jam Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Social sciences categories.
An Introduction To The Rasch Model With Examples In R
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Author : Rudolf Debelak
language : en
Publisher: CRC Press
Release Date : 2022
An Introduction To The Rasch Model With Examples In R written by Rudolf Debelak and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Mathematics categories.
"This book offers a clear, comprehensive introduction to the Rasch model along with practical examples in the free, open-source software R. It is accessible for readers without a background in psychometrics or statistics, while also providing detailed explanations of the relevant mathematical and statistical concepts for readers who want to gain a deeper understanding. Its worked examples in R demonstrate how to apply the methods to real-world examples and how to interpret the resulting output. In addition to motivating and presenting the Rasch model, the book covers different methods for parameter estimation and for assessing fit and differential item functioning (DIF). While focusing on the Rasch model, it also addresses a variety of other dichotomous and polytomous Rasch and item response theory (IRT) models, such as two-parameter logistic (2PL) and Partial Credit models, and extensions, including mixture Rasch models and computerized adaptive testing (CAT). Theory is presented in a self-contained way. All necessary mathematical and statistical background is contained in the chapters and appendices. The book also provides detailed, step-by-step instructions for getting started with R and using the eRm, mirt, TAM and rstan packages for fitting Rasch models"--
The Basics Of Item Response Theory Using R
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Author : Frank B. Baker
language : en
Publisher: Springer
Release Date : 2017-04-25
The Basics Of Item Response Theory Using R written by Frank B. Baker and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-25 with Social Science categories.
This graduate-level textbook is a tutorial for item response theory that covers both the basics of item response theory and the use of R for preparing graphical presentation in writings about the theory. Item response theory has become one of the most powerful tools used in test construction, yet one of the barriers to learning and applying it is the considerable amount of sophisticated computational effort required to illustrate even the simplest concepts. This text provides the reader access to the basic concepts of item response theory freed of the tedious underlying calculations. It is intended for those who possess limited knowledge of educational measurement and psychometrics. Rather than presenting the full scope of item response theory, this textbook is concise and practical and presents basic concepts without becoming enmeshed in underlying mathematical and computational complexities. Clearly written text and succinct R code allow anyone familiar with statistical concepts to explore and apply item response theory in a practical way. In addition to students of educational measurement, this text will be valuable to measurement specialists working in testing programs at any level and who need an understanding of item response theory in order to evaluate its potential in their settings.
Multidimensional Item Response Theory
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Author : M.D. Reckase
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-07-07
Multidimensional Item Response Theory written by M.D. Reckase and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-07-07 with Social Science categories.
Multidimensional Item Response Theory is the first book to give thorough coverage to this emerging area of psychometrics. The book describes the commonly used multidimensional item response theory (MIRT) models and the important methods needed for their practical application. These methods include ways to determine the number of dimensions required to adequately model data, procedures for estimating model parameters, ways to define the space for a MIRT model, and procedures for transforming calibrations from different samples to put them in the same space. A full chapter is devoted to methods for multidimensional computerized adaptive testing. The text is appropriate for an advanced course in psychometric theory or as a reference work for those interested in applying MIRT methodology. A working knowledge of unidimensional item response theory and matrix algebra is assumed. Knowledge of factor analysis is also helpful.
Best Practices In Quantitative Methods
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Author : Jason W. Osborne
language : en
Publisher: SAGE
Release Date : 2008
Best Practices In Quantitative Methods written by Jason W. Osborne and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Language Arts & Disciplines categories.
The contributors to Best Practices in Quantitative Methods envision quantitative methods in the 21st century, identify the best practices, and, where possible, demonstrate the superiority of their recommendations empirically. Editor Jason W. Osborne designed this book with the goal of providing readers with the most effective, evidence-based, modern quantitative methods and quantitative data analysis across the social and behavioral sciences. The text is divided into five main sections covering select best practices in Measurement, Research Design, Basics of Data Analysis, Quantitative Methods, and Advanced Quantitative Methods. Each chapter contains a current and expansive review of the literature, a case for best practices in terms of method, outcomes, inferences, etc., and broad-ranging examples along with any empirical evidence to show why certain techniques are better. Key Features: Describes important implicit knowledge to readers: The chapters in this volume explain the important details of seemingly mundane aspects of quantitative research, making them accessible to readers and demonstrating why it is important to pay attention to these details. Compares and contrasts analytic techniques: The book examines instances where there are multiple options for doing things, and make recommendations as to what is the "best" choice—or choices, as what is best often depends on the circumstances. Offers new procedures to update and explicate traditional techniques: The featured scholars present and explain new options for data analysis, discussing the advantages and disadvantages of the new procedures in depth, describing how to perform them, and demonstrating their use. Intended Audience: Representing the vanguard of research methods for the 21st century, this book is an invaluable resource for graduate students and researchers who want a comprehensive, authoritative resource for practical and sound advice from leading experts in quantitative methods.
Rating Scale Analysis
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Author : Benjamin Drake Wright
language : en
Publisher:
Release Date : 1982
Rating Scale Analysis written by Benjamin Drake Wright and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1982 with Psychological tests categories.
Model Based Clustering Classification And Density Estimation Using Mclust In R
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Author : Luca Scrucca
language : en
Publisher: CRC Press
Release Date : 2023-04-20
Model Based Clustering Classification And Density Estimation Using Mclust In R written by Luca Scrucca and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-20 with Mathematics categories.
Model-based clustering and classification methods provide a systematic statistical approach to clustering, classification, and density estimation via mixture modeling. The model-based framework allows the problems of choosing or developing an appropriate clustering or classification method to be understood within the context of statistical modeling. The mclust package for the statistical environment R is a widely adopted platform implementing these model-based strategies. The package includes both summary and visual functionality, complementing procedures for estimating and choosing models. Key features of the book: An introduction to the model-based approach and the mclust R package A detailed description of mclust and the underlying modeling strategies An extensive set of examples, color plots, and figures along with the R code for reproducing them Supported by a companion website, including the R code to reproduce the examples and figures presented in the book, errata, and other supplementary material Model-Based Clustering, Classification, and Density Estimation Using mclust in R is accessible to quantitatively trained students and researchers with a basic understanding of statistical methods, including inference and computing. In addition to serving as a reference manual for mclust, the book will be particularly useful to those wishing to employ these model-based techniques in research or applications in statistics, data science, clinical research, social science, and many other disciplines.
Spatial Analysis In Geology Using R
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Author : Pedro M. Nogueira
language : en
Publisher: CRC Press
Release Date : 2024-07-01
Spatial Analysis In Geology Using R written by Pedro M. Nogueira and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-01 with Mathematics categories.
The integration of geology with data science disciplines, such as spatial statistics, remote sensing, and geographic information systems (GIS), has given rise to a shift in many natural sciences schools, pushing the boundaries of knowledge and enabling new discoveries in geological processes and earth systems. Spatial analysis of geological data can be used to identify patterns and trends in data, to map spatial relationships, and to model spatial processes. R is a consolidated and yet growing statistical programming language with increasing value in spatial analysis often replacing, with advantage, GIS tools. By providing a comprehensive guide for geologists to harness the power of spatial analysis in R, Spatial Analysis in Geology Using R serves as a tool in addressing real-world problems, such as natural resource management, environmental conservation, and hazard prediction and mitigation. Features: Provides a practical and accessible overview of spatial analysis in geology using R Organised in three independent and complementary parts: Introduction to R, Spatial Analysis with R, and Spatial Statistics and Modelling Applied approach with many detailed examples and case studies using real geological data Presents a collection of R packages that are useful in many geological situations Does not assume any prior knowledge of R; all code are explained in detail Supplemented by a website with all data, code, and examples Spatial Analysis in Geology Using R will be useful to any geological researcher who has acquired basic spatial analysis skills, often using GIS, and is interested in deepening those skills through the use of R. It could be used as a reference by applied researchers and analysts in public, private, or third-sector industries. It could also be used to teach a course on the topic to graduate students or for self-study.